Alcohol impacts an fMRI marker of neural inhibition in humans and rodents [PDF]
NeuroImageInhibitory neuronal activity is a key regulator of brain function and is implicated in numerous developmental and psychiatric disorders. However, measuring inhibition in vivo remains a challenge.
Monami Nishio +8 more
doaj +2 more sources
Improvement in Hurst exponent estimation and its application to financial markets
Financial Innovation, 2022 This research aims to improve the efficiency in estimating the Hurst exponent in financial time series. A new procedure is developed based on equality in distribution and is applicable to the estimation methods of the Hurst exponent.
Miguel Ángel Sánchez +1 more
exaly +2 more sources
Absolute Negative Mobility of Inertial Active Ornstein–Uhlenbeck Particles in Media with Power-Law Correlated Noise [PDF]
EntropyThis study investigates the transport properties of inertial Active Ornstein–Uhlenbeck particles (AOUPs) in a one-dimensional rocking washboard potential externally imposed fractional Gaussian noise (fGn).
Shengna Liu, Kheder Suleiman
doaj +2 more sources
Clustering Arid Rangelands Based on NDVI Annual Patterns and Their Persistence
Remote Sensing, 2022 Rangeland ecosystems comprise more than a third of the global land surface, sustaining essential ecosystem services and livelihoods. In Spain, Southeast Spain includes some of the driest regions; accordingly, rangelands from Murcia and Almeria provinces ...
Ernesto Sanz +6 more
doaj +1 more source
R/S method application in neurological speech disorders analyses [PDF]
Компьютерные исследования и моделирование, 2014 Based on modified rescaled range scale computation algorithm, the technique of Hurst exponent and its characteristic time estimation is proposed. The approach of increase the accuracy and simplification automatic Hurst exponent calculation is developed ...
Nikolay Petrovich Kuzenkov +1 more
doaj +1 more source
Scaling Exponents of Time Series Data: A Machine Learning Approach
Entropy, 2023 In this study, we present a novel approach to estimating the Hurst exponent of time series data using a variety of machine learning algorithms. The Hurst exponent is a crucial parameter in characterizing long-range dependence in time series, and ...
Sebastian Raubitzek +3 more
doaj +1 more source
Characterization of turbulence stability through the identification of multifractional Brownian motions [PDF]
Nonlinear Processes in Geophysics, 2013 Multifractional Brownian motions have become popular as flexible models in describing real-life signals of high-frequency features in geoscience, microeconomics, and turbulence, to name a few.
K. C. Lee
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Cryptocurrencies and Long-Range Trends
International Journal of Financial Studies, 2023 In this study we investigate possible long-range trends in the cryptocurrency market. We employed the Hurst exponent in a sample covering the period from 1 January 2016 to 26 March 2021.
Monica Alexiadou +3 more
doaj +1 more source
Statistical Analysis of Nanofiber Mat AFM Images by Gray-Scale-Resolved Hurst Exponent Distributions
Applied Sciences, 2021 Two-dimensional structures, either periodic or random, can be classified by diverse mathematical methods. Quantitative descriptions of such surfaces, however, are scarce since bijective definitions must be found to measure unique dependency between ...
Tomasz Blachowicz +5 more
doaj +1 more source
Applied Sciences, 2022 We analyze the empirical series of malaria incidence, using the concepts of autocorrelation, Hurst exponent and Shannon entropy with the aim of uncovering hidden variables in those series.
João Sequeira +3 more
doaj +1 more source